TartuNLP @ AXOLOTL-24: 利用分类器输出识别词汇语义中的新意义
摘要
We present our submission to the AXOLOTL-24 shared task. The shared task comprises two subtasks: identifying new senses that words gain with time (when comparing newer and older time periods) and producing the definitions for the identified new senses. We implemented a conceptually simple and computationally inexpensive solution to both subtasks. We trained adapter-based binary classification models to match glosses with usage examples and leveraged the probability output of the models to identify novel senses. The same models were used to match examples of novel sense usages with Wiktionary definitions. Our submission attained third place on the first subtask and the first place on the second subtask.
关键词
引用
@article{arxiv.2407.03861,
title = {TartuNLP @ AXOLOTL-24: Leveraging Classifier Output for New Sense Detection in Lexical Semantics},
author = {Aleksei Dorkin and Kairit Sirts},
journal= {arXiv preprint arXiv:2407.03861},
year = {2024}
}
备注
Accepted to the 5th International Workshop on Computational Approaches to Historical Language Change 2024 (LChange'24)